rm router logits Improve TTOP 3ms (#1407)

### What this PR does / why we need it?

The previous code is
router_logits, _ = self.gate(hidden_states)
hidden_states = get_dp_group().all_gather(hidden_states, 0)
router_logits = get_dp_group().all_gather(router_logits, 0)
I want to change the two all_gathers to one, reduce one all_gather
communication, and make it
hidden_states = get_dp_group().all_gather(hidden_states, 0)
router_logits, _ = self.gate(hidden_states)

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?
bash examples/run_dp_attention_etp16.sh
bash examples/run_dp_attention_etp16_benmark.sh

gsm8k accuracy verification
<img width="1809" alt="截屏2025-06-24 21 53 24"
src="https://github.com/user-attachments/assets/47eace3b-a86b-41b4-9de8-773f57fea33b"
/>



- vLLM version: v0.9.2
- vLLM main:
77f77a951e

---------

Signed-off-by: ttanzhiqiang <389825161@qq.com>

vllm_ascend/utils.py

@@ -439,6 +439,22 @@ class FusedMoEState(Enum):
     NaiveMulticast = 4
 
 
+# TODO(ttanzhiqiang): rm_router_logits
+# dp>1 will trigger
+# In theory, this solution is only applicable to AllGather and AllGatherEP, because in the dp scenario, the previous operation was gate + two communications, and now it is changed to one communication + gate operation, which can save some communication time. In theory, all moe AllGather and AllGatherEP solutions can follow this logic, but now other moe models (qwen3-235b) dp solutions are not adjusted, so use the switch to control it to prevent code errors.
+def get_rm_router_logits_state(ep_size: int, dp_size: int,
+                               is_deepseek_v3_r1: bool):
+    # the fusion operator torch_npu.npu_grouped_matmul_finalize_routing called by allgather ep
+    # only supports deepseek v3/r1
+    if dp_size > 1:
+        if (envs.VLLM_ENABLE_FUSED_EXPERTS_ALLGATHER_EP and ep_size > 1
+                and is_deepseek_v3_r1):
+            return True
+        elif ep_size == 1 and is_deepseek_v3_r1:
+            return True
+    return False
+
+
 # TODO(ttanzhiqiang): all_reduce merge
 # When all_reduce_merge is in progress, shared_experts does not do all_reduce in mlp, but waits until shared_experts+router_experts are completed before doing all_reduce
 # Currently, all_reduce_merge is enabled by default in the AllGather, AllGatherEP and NaiveMulticast scenarios of the deepseek model.